Loading...
Searching...
No Matches
fpfh_omp.h
/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2009, Willow Garage, Inc.
* Copyright (c) 2012-, Open Perception, Inc.
*
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.
* * Neither the name of the copyright holder(s) nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*
* $Id$
*
*/
#pragma once
#include <pcl/features/feature.h>
#include <pcl/features/fpfh.h>
namespace pcl
{
/** \brief FPFHEstimationOMP estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud
* dataset containing points and normals, in parallel, using the OpenMP standard.
*
* \note If you use this code in any academic work, please cite:
*
* - R.B. Rusu, N. Blodow, M. Beetz.
* Fast Point Feature Histograms (FPFH) for 3D Registration.
* In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA),
* Kobe, Japan, May 12-17 2009.
* - R.B. Rusu, A. Holzbach, N. Blodow, M. Beetz.
* Fast Geometric Point Labeling using Conditional Random Fields.
* In Proceedings of the 22nd IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),
* St. Louis, MO, USA, October 11-15 2009.
*
* \attention
* The convention for FPFH features is:
* - if a query point's nearest neighbors cannot be estimated, the FPFH feature will be set to NaN
* (not a number)
* - it is impossible to estimate a FPFH descriptor for a point that
* doesn't have finite 3D coordinates. Therefore, any point that contains
* NaN data on x, y, or z, will have its FPFH feature property set to NaN.
*
* \author Radu B. Rusu
* \ingroup features
*/
template <typename PointInT, typename PointNT, typename PointOutT>
class FPFHEstimationOMP : public FPFHEstimation<PointInT, PointNT, PointOutT>
{
public:
using Ptr = shared_ptr<FPFHEstimationOMP<PointInT, PointNT, PointOutT> >;
using ConstPtr = shared_ptr<const FPFHEstimationOMP<PointInT, PointNT, PointOutT> >;
using Feature<PointInT, PointOutT>::feature_name_;
using Feature<PointInT, PointOutT>::getClassName;
using Feature<PointInT, PointOutT>::indices_;
using Feature<PointInT, PointOutT>::k_;
using Feature<PointInT, PointOutT>::search_parameter_;
using Feature<PointInT, PointOutT>::input_;
using Feature<PointInT, PointOutT>::surface_;
using FeatureFromNormals<PointInT, PointNT, PointOutT>::normals_;
using FPFHEstimation<PointInT, PointNT, PointOutT>::hist_f1_;
using FPFHEstimation<PointInT, PointNT, PointOutT>::hist_f2_;
using FPFHEstimation<PointInT, PointNT, PointOutT>::hist_f3_;
using FPFHEstimation<PointInT, PointNT, PointOutT>::weightPointSPFHSignature;
using PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut;
/** \brief Initialize the scheduler and set the number of threads to use.
* \param[in] nr_threads the number of hardware threads to use (0 sets the value back to automatic)
*/
FPFHEstimationOMP (unsigned int nr_threads = 0)
{
feature_name_ = "FPFHEstimationOMP";
setNumberOfThreads(nr_threads);
}
/** \brief Initialize the scheduler and set the number of threads to use.
* \param[in] nr_threads the number of hardware threads to use (0 sets the value back to automatic)
*/
void
setNumberOfThreads (unsigned int nr_threads = 0);
private:
/** \brief Estimate the Fast Point Feature Histograms (FPFH) descriptors at a set of points given by
* <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in
* setSearchMethod ()
* \param[out] output the resultant point cloud model dataset that contains the FPFH feature estimates
*/
void
computeFeature (PointCloudOut &output) override;
public:
/** \brief The number of subdivisions for each angular feature interval. */
int nr_bins_f1_{11}, nr_bins_f2_{11}, nr_bins_f3_{11};
private:
/** \brief The number of threads the scheduler should use. */
unsigned int threads_;
};
}
#ifdef PCL_NO_PRECOMPILE
#include <pcl/features/impl/fpfh_omp.hpp>
#endif
pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::hist_f3_
Eigen::MatrixXf hist_f3_
Definition fpfh.h:209
pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::hist_f2_
Eigen::MatrixXf hist_f2_
Definition fpfh.h:206
pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::hist_f1_
Eigen::MatrixXf hist_f1_
Definition fpfh.h:203
pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::FPFHEstimation
FPFHEstimation()
Definition fpfh.h:95
pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::weightPointSPFHSignature
void weightPointSPFHSignature(const Eigen::MatrixXf &hist_f1, const Eigen::MatrixXf &hist_f2, const Eigen::MatrixXf &hist_f3, const pcl::Indices &indices, const std::vector< float > &dists, Eigen::VectorXf &fpfh_histogram)
Definition fpfh.hpp:110
pcl::FPFHEstimationOMP::nr_bins_f2_
int nr_bins_f2_
Definition fpfh_omp.h:121
pcl::FPFHEstimationOMP::nr_bins_f3_
int nr_bins_f3_
Definition fpfh_omp.h:121
pcl::FPFHEstimationOMP::ConstPtr
shared_ptr< const FPFHEstimationOMP< PointInT, PointNT, PointOutT > > ConstPtr
Definition fpfh_omp.h:78
pcl::FPFHEstimationOMP::nr_bins_f1_
int nr_bins_f1_
The number of subdivisions for each angular feature interval.
Definition fpfh_omp.h:121
pcl::FPFHEstimationOMP::setNumberOfThreads
void setNumberOfThreads(unsigned int nr_threads=0)
Initialize the scheduler and set the number of threads to use.
Definition fpfh_omp.hpp:52
pcl::FPFHEstimationOMP::PointCloudOut
typename Feature< PointInT, PointOutT >::PointCloudOut PointCloudOut
Definition fpfh_omp.h:92
pcl::FPFHEstimationOMP::Ptr
shared_ptr< FPFHEstimationOMP< PointInT, PointNT, PointOutT > > Ptr
Definition fpfh_omp.h:77
pcl::FPFHEstimationOMP::FPFHEstimationOMP
FPFHEstimationOMP(unsigned int nr_threads=0)
Initialize the scheduler and set the number of threads to use.
Definition fpfh_omp.h:97
pcl::FeatureFromNormals
Definition feature.h:309
pcl::FeatureFromNormals::normals_
PointCloudNConstPtr normals_
A pointer to the input dataset that contains the point normals of the XYZ dataset.
Definition feature.h:349
pcl::Feature
Feature represents the base feature class.
Definition feature.h:107
pcl::Feature::search_parameter_
double search_parameter_
The actual search parameter (from either search_radius_ or k_).
Definition feature.h:234
pcl::Feature::getClassName
const std::string & getClassName() const
Get a string representation of the name of this class.
Definition feature.h:244
pcl::Feature::PointCloudOut
pcl::PointCloud< PointOutT > PointCloudOut
Definition feature.h:124
pcl::Feature::k_
int k_
The number of K nearest neighbors to use for each point.
Definition feature.h:240
pcl::Feature::feature_name_
std::string feature_name_
The feature name.
Definition feature.h:220
pcl::Feature::surface_
PointCloudInConstPtr surface_
An input point cloud describing the surface that is to be used for nearest neighbors estimation.
Definition feature.h:228
pcl::PointCloudOut
pcl::PCLBase< PointInT >::input_
PointCloudConstPtr input_
Definition pcl_base.h:147
pcl::PCLBase< PointInT >::indices_
IndicesPtr indices_
Definition pcl_base.h:150
pcl
Definition convolution.h:46